The use of models and formal analysis techniques at runtime is fundamental to address safety assurance during the system operational stage, when all relevant uncertainties and unknowns can be resolved. This paper presents a novel approach to runtime safety enforcement of software systems based on the MAPE-K control loop architecture for system monitoring and control, and on the Abstract State Machine as runtime model representing the enforcement strategy aimed at preserving or eventually restoring safety. The enforcer software is designed as an autonomic manager that wraps around the software system to monitor and manage unsafe system changes using probing and effecting interfaces provided by the system, so realising grey-box safety enforcement. The proposed approach is supported by a component framework that is here illustrated by means of a case study in the health-care domain.

A Runtime Safety Enforcement Approach by Monitoring and Adaptation / S. Bonfanti, E.M. Riccobene, P. Scandurra (LECTURE NOTES IN ARTIFICIAL INTELLIGENCE). - In: Software Architecture / [a cura di] S. Biffl, E. Navarro, W. Löwe, M. Sirjani, R. Mirandola, D. Weyns. - Prima edizione. - [s.l] : Springer, 2021. - ISBN 978-3-030-86043-1. - pp. 20-36 (( Intervento presentato al 15. convegno ECSA tenutosi a Virtual, Online nel 2021 [10.1007/978-3-030-86044-8_2].

A Runtime Safety Enforcement Approach by Monitoring and Adaptation

E.M. Riccobene
Secondo
;
2021

Abstract

The use of models and formal analysis techniques at runtime is fundamental to address safety assurance during the system operational stage, when all relevant uncertainties and unknowns can be resolved. This paper presents a novel approach to runtime safety enforcement of software systems based on the MAPE-K control loop architecture for system monitoring and control, and on the Abstract State Machine as runtime model representing the enforcement strategy aimed at preserving or eventually restoring safety. The enforcer software is designed as an autonomic manager that wraps around the software system to monitor and manage unsafe system changes using probing and effecting interfaces provided by the system, so realising grey-box safety enforcement. The proposed approach is supported by a component framework that is here illustrated by means of a case study in the health-care domain.
Abstract State Machines@run.time; MAPE-K; Runtime models; Safety enforcement; Self-adaptation
Settore INF/01 - Informatica
2021
Book Part (author)
File in questo prodotto:
File Dimensione Formato  
ECSA2021.pdf

accesso riservato

Tipologia: Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione 1.21 MB
Formato Adobe PDF
1.21 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Bonfanti2021_Chapter_ARuntimeSafetyEnforcementAppro.pdf

accesso riservato

Tipologia: Publisher's version/PDF
Dimensione 1.34 MB
Formato Adobe PDF
1.34 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/919504
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 2
social impact